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11,506 results for “Dynamics”
Data from: Pan-genome dynamics of Pseudomonas gene complements enriched across hexachlorocyclohexane dumpsite
Background: Phylogenetic heterogeneity across Pseudomonas genus is complemented by its diverse genome architecture enriched by accessory genetic elements (plasmids, transposons, and integrons) conferring resistance across this genus. Here, we sequenced a stress tolerant genotype i.e. Pseudomonas sp. strain RL isolated from a hexachlorocyclohexane (HCH) contaminated pond (45 mg of total HCH g−1 sediment) and further compared its gene repertoire with 17 reference ecotypes belonging to P. stutzeri, P. mendocina, P. aeruginosa, P. psychrotolerans and P. denitrificans, representing metabolically diverse ecosystems (i.e. marine, clinical, and soil/sludge). Metagenomic data from HCH contaminated pond sediment and similar HCH contaminated sites were further used to analyze the pan-genome dynamics of Pseudomonas genotypes enriched across increasing HCH gradient. Results: Although strain RL demonstrated clear species demarcation (ANI ≤ 80.03%) from the rest of its phylogenetic relatives, it was found to be closest to P. stutzeri clade which was further complemented functionally. Comparative functional analysis elucidated strain specific enrichment of metabolic pathways like α-linoleic acid degradation and carbazole degradation in Pseudomonas sp. strain RL and P. stutzeri XLDN-R, respectively. Composition based methods (%codon bias and %G + C difference) further highlighted the significance of horizontal gene transfer (HGT) in evolution of nitrogen metabolism, two-component system (TCS) and methionine metabolism across the Pseudomonas genomes used in this study. An intact mobile class-I integron (3,552 bp) with a captured gene cassette encoding for dihydrofolate reductase (dhfra1) was detected in strain RL, distinctly demarcated from other integron harboring species (i.e. P. aeruginosa, P. stutzeri, and P. putida). Mobility of this integron was confirmed by its association with Tnp21-like transposon (95% identity) suggesting stress specific mobilization across HCH contaminated sites. Metagenomics data from pond sediment and recently surveyed HCH adulterated soils revealed the in situ enrichment of integron associated transposase gene (TnpA6100) across increasing HCH contamination (0.7 to 450 mg HCH g−1 of soil). Conclusions: Unlocking the potential of comparative genomics supplemented with metagenomics, we have attempted to resolve the environment and strain specific demarcations across 18 Pseudomonas gene complements. Pan-genome analyses of these strains indicate at astoundingly diverse metabolic strategies and provide genetic basis for the cosmopolitan existence of this taxon.
Data from: Inference of Japanese encephalitis virus ecological and evolutionary dynamics from passive and active virus surveillance
A comprehensive monitoring strategy is vital for tracking the spread of mosquito-borne Japanese encephalitis virus (JEV), the leading cause of viral encephalitis in Asia. Virus detection consists of passive surveillance of primarily humans and swine, and/or active surveillance in mosquitoes, which may be a valuable proxy in providing insights into ecological processes underlying the spread and persistence of JEV. However, it has not been well characterized whether passive surveillance alone can capture the circulating genetic diversity to make reasonable inferences. Here, we develop phylogenetic models to infer JEV host changes, spatial diffusion patterns, and evolutionary dynamics from data collected through active and passive surveillance. We evaluate the feasibility of using JEV sequence data collected from mosquitoes to estimate the migration histories of genotypes GI and GIII. We show that divergence times estimated from this dataset were comparable to estimates from all available data. Increasing the amount of data collected from active surveillance improved time of most recent common ancestor estimates and reduced uncertainty. Phylogenetic estimates using all available data and only mosquito data from active surveillance produced similar results, showing that GI epidemics were widespread and diffused significantly faster between regions than GIII. In contrast, GIII outbreaks were highly structured and unlinked suggesting localized, unsampled infectious sources. Our results show that active surveillance of mosquitoes can sufficiently capture circulating genetic diversity of JEV to confidently estimate spatial and evolutionary patterns. While surveillance of other hosts could contribute to more detailed disease tracking and evaluation, comprehensive JEV surveillance programs should include systematic surveillance in mosquitoes to infer the most complete patterns for epidemiology, and risk assessment.
Data from: Co-evolutionary dynamics between public good producers and cheats in the bacterium Pseudomonas aeruginosa
The production of beneficial public goods is common in the microbial world, and so is cheating – the exploitation of public goods by non-producing mutants. Here, we examine co-evolutionary dynamics between cooperators and cheats and ask whether cooperators can evolve strategies to reduce the burden of exploitation, and whether cheats in turn can improve their exploitation abilities. We evolved cooperators of the bacterium Pseudomonas aeruginosa, producing the shareable iron-scavenging siderophore pyoverdine, together with cheats, defective in pyoverdine production but proficient in uptake. We found that cooperators managed to co-exist with cheats in 56% of all replicates over approximately 150 generations of experimental evolution. Growth and competition assays revealed that co-existence was fostered by a combination of general adaptions to the media and specific adaptions to the co-evolving opponent. Phenotypic screening and whole-genome re-sequencing of evolved clones confirmed this pattern, and suggest that cooperators became less exploitable by cheats because they significantly reduced their pyoverdine investment. Cheats, meanwhile, improved exploitation efficiency through mutations blocking the costly pyoverdine-signalling pathway. Moreover, cooperators and cheats evolved reduced motility, a pattern that likely represents adaptation to laboratory conditions, but at the same time also affects social interactions by reducing strain mixing and pyoverdine sharing. Overall, we observed parallel evolution, where co-existence of cooperators and cheats was enabled by a combination of adaptations to the abiotic and social environment and their interactions.
Data from: Dynamic antagonism between phytochromes and PIF-family bHLHs induces selective reciprocal responses to light and shade in a rapidly responsive transcriptional network in Arabidopsis
Plants respond to shade-modulated light-signals, via the phytochrome (phy) system, by adaptive changes, collectively termed the shade avoidance syndrome (SAS). To examine the roles of the Phy-Interacting bHLH Factors, PIF1, 3, 4 and 5, in relaying this information to the transcriptional network, we compared the genome-wide expression profiles of wild-type and quadruple pif (pifq) mutants in response to shade. The data identify a subset of genes, enriched in transcription-factor-encoding loci, that respond rapidly (within 1 h), in a PIF-dependent manner, to the shade signal, and that contain promoter-located G-box-sequence motifs (CACGTG), known to be preferred PIF binding sites. These genes are thus potential direct targets of phy-PIF signaling that function in the primary transcriptional circuitry controlling downstream response-elaboration. A second subset of PIF-dependent, early-response genes, lacking G-box motifs, are enriched for auxin-responsive loci, suggestive of being indirect targets of phy-PIF signaling involved in the rapid cell-expansion known to be induced by shade. A meta-analysis comparing deetiolation- and shade-responsive transcriptomes identifies a further subset of G-box-containing genes that reciprocally display rapid repression and induction in response to light and shade signals at the inception of deetiolation and shade-avoidance, respectively. Collectively, these data define a core set of transcriptional and hormonal (auxin, cytokinin) processes that appear to be dynamically poised to react rapidly to changes in the light environment via perturbations in the mutually antagonistic actions of the phys and PIFs. Data from comparative analysis of the quadruple pifq and all triple pif-mutant combinations in response to light and shade, confirm that the PIF-quartet members act with overlapping redundancy on seedling morphogenesis and transcriptional regulation, but that the individual PIFs contribute differentially to these responses.
Data from: Force and torque on spherical particles in micro-channel flows using computational fluid dynamics
To delineate the influence of hemodynamic force on cell adhesion processes, model in vitro fluidic assays that mimic physiological conditions are commonly employed. Herein, we offer a framework for solution of the three-dimensional Navier–Stokes equations using computational fluid dynamics (CFD) to estimate the forces resulting from fluid flow near a plane acting on a sphere that is either stationary or in free flow, and we compare these results to a widely used theoretical model that assumes Stokes flow with a constant shear rate. We find that while the full three-dimensional solutions using a parabolic velocity profile in CFD simulations yield similar translational velocities to those predicted by the theoretical method, the CFD approach results in approximately 50% larger rotational velocities over the wall shear stress range of 0.1–5.0 dynes cm−2. This leads to an approximately 25% difference in force and torque calculations between the two methods. When compared with experimental measurements of translational and rotational velocities of microspheres or cells perfused in microfluidic channels, the CFD simulations yield significantly less error. We propose that CFD modelling can provide better estimations of hemodynamic force levels acting on perfused microspheres and cells in flow fields through microfluidic devices used for cell adhesion dynamics analysis.
Data from: Host use dynamics in a heterogeneous fitness landscape generates oscillations in host range and diversification
Colonization of novel hosts is thought to play an important role in parasite diversification, yet little consensus has been achieved about the macroevolutionary consequences of changes in host use. Here we offer a mechanistic basis for the origins of parasite diversity by simulating lineages evolved in silico. We describe an individual-based model in which (i) parasites undergo sexual reproduction limited by genetic proximity, (ii) hosts are uniformly distributed along a one-dimensional resource gradient, and (iii) host use is determined by the interaction between the phenotype of the parasite and a heterogeneous fitness landscape. We found two main effects of host use on the evolution of a parasite lineage. First, the colonization of a novel host allowed parasites to explore new areas of the resource space, increasing phenotypic and genotypic variation. Second, hosts produced heterogeneity in the parasite fitness landscape, which led to reproductive isolation and therefore, speciation. As a validation of the model, we analyzed empirical data from Nymphalidae butterflies and their host plants. We then assessed the number of hosts used by parasite lineages and the diversity of resources they encompass. In both simulated and empirical systems, host diversity emerged as the main predictor of parasite species richness.
Data from: Intrinsic and extrinsic drivers of source-sink dynamics
Many factors affect the presence and exchange of individuals among subpopulations and influence not only the emergence, but the strength of ensuing source–sink dynamics within metapopulations. Yet their relative contributions remain largely unexplored. To help identify the characteristics of empirical systems that are likely to exhibit strong versus weak source–sink dynamics and inform their differential management, we compared the relative roles of influential factors in strengthening source–sink dynamics. In a series of controlled experiments within a spatially explicit individual-based model framework, we varied patch quality, patch size, the dispersion of high- and low-quality patches, population growth rates, dispersal distances, and environmental stochasticity in a factorial design. We then recorded source–sink dynamics that emerged from the simulated habitat and population factors. Long-term differences in births and deaths were quantified for sources and sinks in each system and used in a statistical model to rank the influences of key factors. Our results suggest that systems with species capable of rapid growth, occupying habitat patches with more disparate qualities, with interspersed higher- and lower-quality habitats, and that experience relatively stable environments (i.e., fewer negative perturbations) are more likely to exhibit strong source–sink dynamics. Strong source–sink dynamics emerged under diverse combinations of factors, suggesting that simple inferences of process from pattern will likely be inadequate to predict and assess the strength of source–sink dynamics. Our results also suggest that it may be more difficult to detect and accurately measure source–sink dynamics in slow-growing populations, highly variable environments, and where a subtle gradient of habitat quality exists.
Data from: The dynamic role of genetics on cortical patterning during childhood and adolescence
Longitudinal imaging and quantitative genetic studies have both provided important insights into the nature of human brain development. In the present study we combine these modalities to obtain dynamic anatomical maps of the genetic contributions to cortical thickness through childhood and adolescence. A total of 1,748 anatomic MRI scans from 792 healthy twins and siblings were studied with up to eight time points per subject. Using genetically informative latent growth curve modeling of 81,924 measures of cortical thickness, changes in the genetic contributions to cortical development could be visualized across the age range at high resolution. There was highly statistically significant (P < 0.0001) genetic variance throughout the majority of the cerebral cortex, with the regions of highest heritability including the most evolutionarily novel regions of the brain. Dynamic modeling of changes in heritability over time demonstrated that the heritability of cortical thickness increases gradually throughout late childhood and adolescence, with sequential emergence of three large regions of high heritability in the temporal poles, the inferior parietal lobes, and the superior and dorsolateral frontal cortices.
Data from: The dynamics of niche evolution upon abrupt environmental change
Abrupt environmental changes are of particular interest to understand how species can quickly evolve at the boundary of their current niche. In particular the 'sliding niche' model, wherein a niche shifts globally toward the new condition, has been utilized in understanding and modeling this process. Here, we investigate the dynamics of relative fitness change in four evolutionary replicates of Escherichia coli populations exposed to an extreme pH shift. We analyzed these changes at generations 500, 1000 and 2000 to determine, whether niche global deformations fully capture the temporal dynamics of niche evolution. Strikingly, this analysis reveals that fitness variations can indeed be attributed to simple and global deformation of an underlying simple niche template. Analysis from two experimental replicates displays a transient increase in niche width, consistent with recent theory considering plasticity evolution in the context of an abrupt environmental change. We term this scenario the 'sidestep niche model'.
Data from: Higher frequency of social learning in China than in the West shows cultural variation in the dynamics of cultural evolution
Cultural evolutionary models have identified a range of conditions under which social learning (copying others) is predicted to be adaptive relative to asocial learning (learning on one's own), particularly in humans where socially learned information can accumulate over successive generations. However, cultural evolution and behavioural economics experiments have consistently shown apparently maladaptive under-utilization of social information in Western populations. Here we provide experimental evidence of cultural variation in people's use of social learning, potentially explaining this mismatch. People in mainland China showed significantly more social learning than British people in an artefact-design task designed to assess the adaptiveness of social information use. People in Hong Kong, and Chinese immigrants in the UK, resembled British people in their social information use, suggesting a recent shift in these groups from social to asocial learning due to exposure to Western culture. Finally, Chinese mainland participants responded less than other participants to increased environmental change within the task. Our results suggest that learning strategies in humans are culturally variable and not genetically fixed, necessitating the study of the 'social learning of social learning strategies' whereby the dynamics of cultural evolution are responsive to social processes, such as migration, education and globalization.
Data from: Eco-evolutionary dynamics in metacommunities: ecological inheritance, helping within species, and harming between species
Understanding selection on intra- and inter-specific interactions that take place in dispersal-limited communities is a challenge for ecology and evolutionary biology. The problem is that local demographic stochasticity generates eco-evolutionary dynamics that are generally too complicated to make tractable analytical investigations. Here, we circumvent this problem by approximating the selection gradient on a quantitative trait that influences local community dynamics, assuming that such dynamics are deterministic with a stable fixed point. We nonetheless incorporate unavoidable kin selection effects arising from demographic stochasticity. Our approximation reveals that selection depends on how an individual expressing a trait-change influences: (1) its own fitness and the fitness of its current relatives; and (2) the fitness of its downstream relatives through modifications of local ecological conditions (i.e., through ecological inheritance). Mathematically, the effects of ecological inheritance on selection are captured by dispersal-limited versions of press-perturbations of community ecology. We use our approximation to investigate the evolution of helping within- and harming between-species when these behaviours influence demography. We find that altruistic helping evolves more readily when intra-specific competition is for material resources rather than for space because in this case, the costs of kin competition tend to paid by downstream relatives. Similarly, altruistic harming between species evolves when it alleviates downstream relatives from inter-specific competition. Beyond these examples, our approximation can help better understand the influence of ecological inheritance on a variety of eco-evolutionary dynamics in metacommunities, from consumer-resource and predator-prey coevolution to selection on mating systems with demographic feedbacks.
Data from: Growth mode and carbon source impact the surfaceome dynamics of Lactobacillus rhamnosus GG
Bacterial biofilms have clear implications in disease and in food applications involving probiotics. Here, we show that switching the carbohydrate source from glucose to fructose increased the biofilm formation and the total surface-antigenicity of a well-known probiotic, Lactobacillus rhamnosus GG. Surfaceomes (all cell surface-associated proteins) of GG cells grown with glucose and fructose in planktonic and biofilm cultures were identified and compared, which indicated carbohydrate source-dependent variations, especially during biofilm growth. The most distinctive differences under these conditions were detected with several surface adhesins (e.g., MBF, SpaC pilus protein and penicillin-binding proteins), enzymes (glycoside hydrolases, PrsA, PrtP, PrtR and HtrA) and moonlighting proteins (glycolytic, transcription/translation and stress-associated proteins, r-proteins, tRNA synthetases, Clp family proteins, PepC, PepN and PepA). The abundance of several known adhesins and candidate moonlighters, including enzymes acting on casein-derived peptides (ClpP, PepC and PepN), increased in the biofilm cells grown on fructose, from which the surface-associated aminopeptidase activity mediated by PepC and PepN was further confirmed by an enzymatic assay. The mucus binding factor (MBF) was found most abundant in fructose grown biofilm cells whereas SpaC adhesin was identified specifically from planktonic cells growing on fructose. An additional indirect ELISA indicated both growth mode- and carbohydrate-dependent differences in abundance of SpaC, whereas the overall adherence of GG assessed with porcine mucus indicated that the carbon source and the growth mode affected mucus adhesion. The adherence of GG cells to mucus was almost completely inhibited by anti-SpaC antibodies regardless of growth mode and/or carbohydrate source, indicating the key role of the SpaCBA pilus in adherence under the tested conditions. Altogether, our results suggest that carbon source and growth mode coordinate mechanisms shaping the proteinaceous composition of GG cell surface, which potentially contributes to resistance, nutrient acquisition and cell-cell interactions under different conditions. In conclusion, the present study shows that different growth regimes and conditions can have a profound impact on the adherent and antigenic features of GG, thereby providing new information on how to gain additional benefits from this probiotic.
Data from: The within-host dynamics of infection in trans-generationally primed flour beetles
Many taxa exhibit plastic immune responses initiated after primary microbial exposure that provide increased protection against disease-induced mortality and the fitness costs of infection. In several arthropod species, this protection can even be passed from parents to offspring through a phenomenon called trans-generational immune priming. Here, we first demonstrate that trans-generational priming is a repeatable phenomenon in flour beetles (Tribolium castaneum) primed and infected with Bacillus thuringiensis (Bt). We then quantify the within-host dynamics of microbes and host physiological responses in infected offspring from primed and unprimed mothers by monitoring bacterial density and using mRNA-seq to profile host gene expression, respectively, over the acute infection period. We find that priming increases inducible resistance against Bt around a critical temporal juncture where host septicaemic trajectories, and consequently survival, may be determined in unprimed individuals. Our results identify a highly differentially expressed biomarker of priming, containing an EIF4-e domain, in uninfected individuals, as well as several other candidate genes. Moreover, the induction and decay dynamics of gene expression over time suggest a metabolic shift in primed individuals. The identified bacterial and gene expression dynamics are likely to influence patterns of bacterial fitness and disease transmission in natural populations.
Data from: Local adaptation at higher trophic levels: contrasting hyperparasite-pathogen infection dynamics in the field and laboratory
Predicting and controlling infectious disease epidemics is a major challenge facing the management of agriculture, human and wildlife health. Coevolutionarily derived patterns of local adaptation among pathogen populations have the potential to generate variation in disease epidemiology, however studies of local adaptation in disease systems have mostly focused on interactions between competing pathogens or pathogens and their hosts. In nature, parasites and pathogens are also subject to attack by hyperparasitic natural enemies that can severely impact upon their infection dynamics. However, few studies have investigated if this interaction varies across combinations of pathogen-hyperparasite strains, and if this influences hyperparasite incidence in natural pathogen populations. Here, we test if the association between a hyperparasitic fungus, Ampelomyces quisqualis, and a single powdery mildew host, Podosphaera plantaginis, varies among genotype combinations, and whether this drives hyperparasite incidence in nature. Laboratory inoculation studies reveal that genotype, genotype x genotype interactions, and local adaptation affect hyperparasite infection. However, observations of a natural pathogen metapopulation reveal that spatial rather than genetic factors predict the risk of hyperparasite presence. Our results highlight how sensitive the outcome of biocontrol using hyperparasites is to selection of hyperparasite strains.
Data from: Linking intra-specific trait variation to community abundance dynamics improves ecological predictability by revealing a growth-defence trade-off
1.Intraspecific trait change, including altered behaviour or morphology, can drive temporal variation in inter-specific interactions and population dynamics. In turn, variation in species' interactions and densities can alter the strength and direction of trait change. The resulting feedback between species′ traits and abundance permits a wide range of community dynamics that would not be expected from ecological theories purely based on species abundances. Despite the theoretical importance of these interrelated processes, unambiguous experimental evidence of how intraspecific trait variation modifies species interactions and population dynamics and how this feeds back to influence trait variation is currently required. 2.We investigate the role of trait-mediated demography in determining community dynamics and examine how ecological interactions influence trait change. We concurrently monitored the dynamics of community abundances and individual traits in an experimental microbial predator-prey-resource system. Using this data, we parameterized a trait dependent community model to identify key ecologically relevant traits and to link trait dynamics with those of species abundances. 3.Our results provide clear evidence of a feedback between trait change, demographic rates and species dynamics. The inclusion of trait-abundance feedbacks into our population model improved the predictability of ecological dynamics from r-squared of 34% to 57% and confirmed theoretical expectations of density dependent population growth and species interactions in the system. 4.Additionally, our model revealed that the feedbacks were underpinned by a trade-off between population growth and anti-predatory defence. High predator abundance was linked to a reduction in prey body size. This prey size decrease was associated with a reduction in its rate of consumption by predators and a decrease in its resource consumption. 5.Modelling trait-abundance feedbacks allowed us to pinpoint the underlying life history trade-off which links trait and abundance dynamics. These results show that accounting for trait-abundance feedbacks has the potential to improve understanding and predictability of ecological dynamics.
Data from: Dynamic relocalization of replication origins by Fkh1 requires execution of DDK function and Cdc45 loading at origins
Chromosomal DNA elements are organized into spatial domains within the eukaryotic nucleus. For example, sites actively undergoing DNA replication, high-level transcription, and repair of double-strand breaks coalesce into foci, although the significance and mechanisms giving rise to these dynamic structures are poorly understood. In S. cerevisiae, replication origins exhibit characteristic subnuclear localizations prior to S phase that anticipate their initiation timing and/or efficiency during S phase: origins found within the nuclear interior in G1 phase initiate early and efficiently in S phase while origins found associated with the nuclear periphery in G1 phase initiate later and less efficiently. In this study, we link interior localization of replication origins in G1 phase with Fkh1 activity, which is required for their early replication timing. Using a Fkh1-dependent origin relocalization assay, we determine that execution of Dbf4-dependent kinase function, including Cdc45 loading, results in dynamic relocalization of a replication origin from the nuclear periphery to the interior in G1 phase. Origin mobility increases substantially with Fkh1-driven relocalization. These findings provide novel molecular insight into the mechanisms that govern dynamics and spatial organization of DNA replication origins and possibly other functional DNA elements.
Data from: A multi-state dynamic occupancy model to estimate local colonization-extinction rates and patterns of co-occurrence between two or more interacting species
1. Although ecology is rife with theory that explores how multiple species co-occur through space and time, the field lacks robust statistical models to parameterize this theory with empirical data, particularly when species are detected imperfectly and data are collected as a time-series. 2. We address this need by developing an occupancy model that estimates local colonization and extinction rates for two or more interacting species when data are collected across multiple sampling occasions. This model estimates how community composition at a site may change across sampling occasions by assuming the latent occupancy state is a categorical random variable. We used a multinomial-logit model to parameterize species-specific parameters and pairwise interactions between species, both of which can be made a function of covariates. These transition probabilities between community states can then be converted to occupancy or co-occurrence probabilities to determine how community composition varies along an environmental gradient or through time. 3. As an example, we estimate patterns of co-occurrence between coyote (Canis latrans), Virginia opossum (Didelphis virginiana), and raccoon (Procyon lotor) in Chicago, Illinois, USA with data from a multi-year camera trapping study. Models with pairwise interactions between species greatly out performed models that assumed independence between species. Opossum and raccoon, for example, were far less likely to go extinct in habitat patches where coyotes were present. 4. Community composition at a site depends on species interactions and the local environment. Our model can separate such effects by estimating the underlying processes that define species occurrence patterns. As a result, our model can more explicitly quantify a wide range of ecological dynamics and therefore be used to empirically test ecological theory, such as estimating priority effects at a site or turnover rates between species, both of which can be made to vary as a function of covariates.
Data from: Managing seagrass resilience under cumulative dredging affecting light: predicting risk using dynamic Bayesian networks
Coastal development is contributing to ongoing declines of ecosystems globally. Consequently, understanding the risks posed to these systems, and how they respond to successive disturbances, is paramount for their improved management. We study the cumulative impacts of maintenance dredging on seagrass ecosystems as a canonical example. Maintenance dredging causes disturbances lasting weeks to months, often repeated at yearly intervals. We present a risk-based modelling framework for time varying complex systems centred around a dynamic Bayesian network (DBN). Our approach estimates the impact of a hazard on a system's response in terms of resistance, recovery and persistence, commonly used to characterise the resilience of a system. We consider whole-of-system interactions including light reduction due to dredging (the hazard), the duration, frequency and start time of dredging, and ecosystem characteristics such as the life-history traits expressed by genera and local environmental conditions. The impact on resilience of dredging disturbances is evaluated using a validated seagrass ecosystem DBN for meadows of the genera Amphibolis (Jurien Bay, WA, Australia), Halophila (Hay Point, Qld, Australia) and Zostera (Gladstone, Qld, Australia). Although impacts varied by combinations of dredging parameters and the seagrass meadows being studied, in general, 3 months of duration or more, or repeat dredging every 3 or more years, were key thresholds beyond which resilience can be compromised. Additionally, managing light reduction to less than 50% can significantly decrease one or more of loss, recovery time and risk of local extinction, especially in the presence of cumulative stressors. Synthesis and applications. Our risk-based approach enables managers to develop thresholds by predicting the impact of different configurations of anthropogenic disturbances being managed. Many real-world maintenance dredging requirements fall within these parameters, and our results show that such dredging can be successfully managed to maintain healthy seagrass meadows in the absence of other disturbances. We evaluated opportunities for risk mitigation using time windows; periods during which the impact of dredging stress did not impair resilience.
Data from: Comparative dynamics of microglialand glioma cell motility at the infiltrative margin of brain tumours
Microglia are a major cellular component of gliomas, and abundant in the centre of the tumour and at the infiltrative margins. While glioma is a notoriously infiltrative disease, the dynamics of microglia and glioma migratory patterns have not been well characterized. To investigate the migratory behaviour of microglia and glioma cells at the infiltrative edge, we performed two-colour time-lapse fluorescence microscopy of brain slices generated from a platelet-derived growth factor-B (PDGFB)-driven rat model of glioma, in which glioma cells and microglia were each labelled with one of two different fluorescent markers. We used mathematical techniques to analyse glioma cells and microglia motility with both single cell tracking and particle image velocimetry (PIV). Our results show microglia motility is strongly correlated with the presence of glioma, while the correlation of the speeds of glioma cells and microglia was variable and weak. Additionally, we showed that microglia and glioma cells exhibit different types of diffusive migratory behaviour. Microglia movement fit a simple random walk, while glioma cell movement fits a super diffusion pattern. These results show that glioma cells stimulate microglia motility at the infiltrative margins, creating a correlation between the spatial distribution of glioma cells and the pattern of microglia motility.
Data from: Transcriptome and proteome dynamics of a light-dark synchronized bacterial cell cycle
BACKGROUND: Growth of the ocean's most abundant primary producer, the cyanobacterium Prochlorococcus, is tightly synchronized to the natural 24-hour light-dark cycle. We sought to quantify the relationship between transcriptome and proteome dynamics that underlie this obligate photoautotroph's highly choreographed response to the daily oscillation in energy supply. METHODOLOGY/PRINCIPAL FINDINGS: Using Illumina RNA-sequencing transcriptomics and mass spectrometry-based quantitative proteomics, we measured timecourses of paired mRNA-protein abundances for 312 genes every 2 hours over a light-dark cycle. These temporal expression patterns reveal strong oscillations in transcript abundance that are broadly damped at the protein level, with mRNA levels varying on average 2.3 times more than the corresponding protein. The single strongest observed protein-level oscillation is in a ribonucleotide reductase, which may reflect a defense strategy against phage infection. The peak in abundance of most proteins also lags that of their transcript by 2-8 hours, and the two are completely antiphase for some genes. While abundant antisense RNA was detected, it apparently does not account for the observed divergences between expression levels. The redirection of flux through central carbon metabolism from daytime carbon fixation to nighttime respiration is associated with quite small changes in relative enzyme abundances. CONCLUSIONS/SIGNIFICANCE: Our results indicate that expression responses to periodic stimuli that are common in natural ecosystems (such as the diel cycle) can diverge significantly between the mRNA and protein levels. Protein expression patterns that are distinct from those of cognate mRNA have implications for the interpretation of transcriptome and metatranscriptome data in terms of cellular metabolism and its biogeochemical impact.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.